Conventionally, some devices capable of detecting a vehicle being in peripheral of the vehicle itself by using an on-vehicle camera and notifying the driver of the presence thereof, have been disclosed. As a typical algorithm of a vehicle detection technology for detecting a peripheral vehicle from an image captured by the on-vehicle camera, a method using pattern matching, with which the features of the vehicle previously set in an image format or a vector format are compared with various partial regions in the image and the presence or absence of the vehicle is determined, is known.
In such a method, however, if checking for the entire region of the image is performed even when there are numerous shapes and sizes of the features of vehicles, large amounts of calculation for checking are needed. Therefore, it has been difficult to detect a vehicle in real time.
In view of this, a vehicle detection technology has been known, and with this method, an assumed region which is assumed to be corresponding to a vehicle in an image is detected by using an algorithm having less calculation amount and pattern matching is applied for only this assumed region.
As algorithms for detecting the assumed region used in the foregoing vehicle detection technology, an algorithm for extracting a pair of vertical edges corresponding to both sides of a vehicle from the image and detecting an assumed region based on that, an algorithm for extracting a black region from the image and detecting an assumed region based on the shape thereof, and an algorithm for extracting a portion where the luminance variation is large in the longitudinal direction from the image and detecting an assumed region based on a variance value of a pixel value within a local region set so as to include the portion, are cited.
As the algorithm for extracting a pair of vertical edges, Patent document 1 discloses a method for detecting a vehicle by verifying how much a pair of vertical edge line segments and horizontal edge line segments existing therebetween satisfies a reference relating to a vehicle respectively. Further, Non-patent document 1 discloses the method for determining whether it is a vehicle or not by voting for positions in a Hough space corresponding to the center position of a pair of vertical edge line segments and inputting the image of the partial region near the position getting a lot of votes into a neutral network discriminator.
As the algorithm for extracting a black region, Patent documents 2 and 3 disclose a method for binarizing a monochrome image, after expanding the black region of the monochrome image so as to divide into a black region and a white region, and determining whether or not the black region corresponds to a vehicle based on the area, the barycenter position, the aspect ratio and the like of the black region after a denoising processing.
As the algorithm for extracting a portion in which luminance variation is large in the longitudinal direction, Patent document 4 discloses the method for detecting a longitudinal axis coordinate that a pixel value indicating luminance changes drastically in a longitudinal direction, and determining that, if a variance value of a pixel value within a partial region set so as to include the longitudinal axis coordinate is larger than a reference value, the partial region corresponds to a vehicle. Patent document 4 described that this method is capable of discriminating a shadow of the vehicle from shadows of trees and the like by being based on the variance value in the partial region.    Non-patent document 1: “Vehicle Detection Technology Using Method of Feature Space Projection of Edge Pair”, VIEW 2005, Proceedings of Vision Engineering Workshop, by The Japan Society for Precision Engineering p. 160-165    Patent Document 1: Japanese Patent No. 3072730    Patent Document 2: Japanese Patent Application Laid-open No. H09-016751    Patent Document 3: Japanese Patent Application Laid-open No, H09-128548    Patent Document 4: Japanese Patent No. 3069952